def __init__(self, json_decoder: JSONDataBodyDecoder, wrapped: BaseStep, json_encoder: JSONDataResponseEncoder, route='/'): Pipeline.__init__(self, [json_decoder, wrapped, json_encoder]) self.route: str = route
def __init__( self, pipeline: Union[BaseStep, NamedTupleList], validation_size: float = 0.0, batch_size: int = None, batch_metrics: Dict[str, Callable] = None, shuffle_in_each_epoch_at_train: bool = True, seed: int = None, n_epochs: int = 1, epochs_metrics: Dict[str, Callable] = None, scoring_function: Callable = None, metrics_plotting_step: BaseStep = None, cache_folder: str = None, print_epoch_metrics=False, print_batch_metrics=False ): if epochs_metrics is None: epochs_metrics = {} if batch_metrics is None: batch_metrics = {} self.final_scoring_metric = scoring_function self.epochs_metrics = epochs_metrics self.n_epochs = n_epochs self.shuffle_in_each_epoch_at_train = shuffle_in_each_epoch_at_train self.batch_size = batch_size self.batch_metrics = batch_metrics self.validation_size = validation_size self.metrics_plotting_step = metrics_plotting_step self.print_batch_metrics = print_batch_metrics self.print_epoch_metrics = print_epoch_metrics wrapped = pipeline wrapped = self._create_mini_batch_pipeline(wrapped) if shuffle_in_each_epoch_at_train: wrapped = TrainShuffled(wrapped=wrapped, seed=seed) wrapped = self._create_validation_split(wrapped) wrapped = self._create_epoch_repeater(wrapped) BaseStep.__init__(self) Pipeline.__init__(self, [wrapped], cache_folder=cache_folder)
def __init__(self, steps: NamedTupleList): Pipeline.__init__(self, steps) self.teared_down = False
def __init__(self, wrapped, seed=None): Pipeline.__init__(self, [TrainOnlyWrapper(DataShuffler(seed=seed)), wrapped])